从1993年到2023年,对Helicobacter pylori疫苗开发的文献分析分析
Yeqing Lei1, Xiaochen Liu2, Qin Du1,2
1Department of Gastroenterology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.
Frontiers in microbiology
|April 1, 2025
概括
这份对Helicobacter pylori疫苗研究的图书统计分析揭示了出版物上升的趋势,并确定了关键贡献者和新兴的边界. 它强调了需要有效的治疗方法和新型抗原组合来开发H. pylori疫苗的需求.
科学领域:
- * 传染病研究 传染病研究
- * 疫苗学 疫苗学 疫苗学
- * 图书识别分析
背景情况:
- * 杆菌感染影响全球一半人口,对健康构成重大挑战.
- *开发H. pylori疫苗是一个关键的预防策略.
- *本研究分析了1993年至2023年间的H. pylori疫苗研究趋势.
研究的目的:
- *对H.pylori疫苗研究进行第一个图书统计分析.
- * 确定H. pylori疫苗开发中的当前趋势,关键贡献者和研究前沿.
- *为研究人员提供有价值的数据,以加快H. pylori疫苗的开发.
主要方法:
- *对与H. pylori疫苗相关的文章和评论进行文献计量分析.
- *数据来源于1993年至2023年的Web of Science核心集合 (WoSCC) 的数据.
- *使用Microsoft Excel,CiteSpace和VOS查看器进行的分析.
主要成果:
- *分析了1,199个出版物,显示出版物和引用的趋势越来越大.
- * 美国是出版物,引文和国际合作的主要贡献者.
- *关键的研究领域包括有效的治疗和多表位疫苗,新型抗原组合 (例如,UreB,外膜囊泡) 代表了边界.
结论:
- *本研究提供了对H. pylori疫苗研究领域的全面概述.
- * 它确定了当前的研究方向和新兴的前沿.
- *这些发现旨在支持研究人员推进H. pylori疫苗的开发.
更多相关视频
相关概念视频
Statistical Analysis: Overview
5.3K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
5.3K
Analysis of Population Pharmacokinetic Data
203
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
203
Chi-square Analysis
35.8K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
35.8K
Statistical Methods to Analyze Parametric Data: ANOVA
251
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
251
Statistical Significance
19.9K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
19.9K
Biostatistics: Overview
208
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Discrete variables are...
208


